Connect physical world to your api and collect data.
6 resources to take control of your Objects, Flows, Dashboards, Snippets, Rules, and Mqtts topics. Live, eat, and breathe the API-first lifestyle of t6. Easy to Use api - easy to connect and very simple to integrate into your device.
Supervised Machine Learning (SML) is a widely used technique in machine learning, and t6 IoT plays a pivotal role in its implementation. With t6 IoT, the process of building and training SML models involves harnessing labeled examples collected from Internet of Things (IoT) devices.
t6 comes with and handfull set of EDA apis. Today the implementation is still in progress but give the opportunity to begin Exploring timeseries datapoints from a specific flow.
Sensor Fusion is the process of merging multiple values together. Data Fusion on t6 allows to combine multiple measures from several Flows (Tracks) onto another Flow (Primary). This "Fusion" will be made according to an algorithm defined directly on the Primary Flow. Data Fusion is working after the preprocessor engine is transforming the value. And after the Fusion, the value can optionaly be saved to the Primary Flow before it goes to the Decision Rule engine.
t6 is focused on timeseries, Data-annotation process is classifying Datapoints from Flows using categories. Annotations and Categories are going to be used in the Exploratory Data Analysis process.
Tagged on #recipe, #rules, #geofencing,
Sat, Jul 15, 2023
Geofencing is a powerful feature within the t6 IoT platform that revolutionizes location-based capabilities. By creating virtual boundaries around specific locations using perimeter area zones, t6 geofencing empowers you to streamline operations, improve security, and deliver personalized experiences.
Tagged on #Predictive Maintenance,
Sun, Jul 9, 2023
This recipe article provides a step-by-step guide on implementing predictive maintenance with t6 and temperature sensors. We will walk you through the process of setting up the t6 IoT Platform, collecting and preprocessing temperature data, building and training a predictive maintenance model, and triggering alerts based on model predictions. By the end of this article, you will have the knowledge and tools to optimize equipment reliability, reduce downtime, and revolutionize your maintenance strategies.